六十七、Spark-两种运行方式（本地运行，提交集群运行）

本地运行：在IDEA中直接运行控制台输出结果即可

集群运行：在本地将程序打包为 jar，提交至集群运行其程序（将结果上传至hdfs）

文章目录

一、本地运行spark程序

二、集群运行spark程序

一、本地运行spark程序

        1、pom依赖

        注：依赖配置项及其版本一定要与集群环境相适配

      <?xml version="1.0" encoding="UTF-8"?>
      <project xmlns="http://maven.apache.org/POM/4.0.0"
              xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
              xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
         <modelVersion>4.0.0</modelVersion>
         <groupId>cn.itcast</groupId>
         <artifactId>SparkDemo</artifactId>
         <version>1.0-SNAPSHOT</version>
         <repositories>
             <repository>
                 <id>aliyun</id>
                 <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
             </repository>
             <repository>
                 <id>apache</id>
                 <url>https://repository.apache.org/content/repositories/snapshots/</url>
             </repository>
             <repository>
                 <id>cloudera</id>
                 <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
             </repository>
         </repositories>
         <properties>
             <encoding>UTF-8</encoding>
             <maven.compiler.source>1.8</maven.compiler.source>
             <maven.compiler.target>1.8</maven.compiler.target>
             <scala.version>2.12.11</scala.version>
             <spark.version>3.0.1</spark.version>
             <hadoop.version>2.7.5</hadoop.version>
         </properties>
         <dependencies>
             <!--依赖Scala语言-->
             <dependency>
                 <groupId>org.scala-lang</groupId>
                 <artifactId>scala-library</artifactId>
                 <version>${scala.version}</version>
             </dependency>
             <!--SparkCore依赖-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-core_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!-- spark-streaming-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-streaming_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!--spark-streaming+Kafka依赖-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-streaming-kafka-0-10_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!--SparkSQL依赖-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-sql_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!--SparkSQL+ Hive依赖-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-hive_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-hive-thriftserver_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!--StructuredStreaming+Kafka依赖-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-sql-kafka-0-10_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <!-- SparkMlLib机器学习模块,里面有ALS推荐算法-->
             <dependency>
                 <groupId>org.apache.spark</groupId>
                 <artifactId>spark-mllib_2.12</artifactId>
                 <version>${spark.version}</version>
             </dependency>
             <dependency>
                 <groupId>org.apache.hadoop</groupId>
                 <artifactId>hadoop-client</artifactId>
                 <version>2.7.5</version>
             </dependency>
             <dependency>
                 <groupId>com.hankcs</groupId>
                 <artifactId>hanlp</artifactId>
                 <version>portable-1.7.7</version>
             </dependency>
             <dependency>
                 <groupId>mysql</groupId>
                 <artifactId>mysql-connector-java</artifactId>
                 <version>8.0.23</version>
             </dependency>
             <dependency>
                 <groupId>redis.clients</groupId>
                 <artifactId>jedis</artifactId>
                 <version>2.9.0</version>
             </dependency>
             <dependency>
                 <groupId>com.alibaba</groupId>
                 <artifactId>fastjson</artifactId>
                 <version>1.2.47</version>
             </dependency>
             <dependency>
                 <groupId>org.projectlombok</groupId>
                 <artifactId>lombok</artifactId>
                 <version>1.18.2</version>
                 <scope>provided</scope>
             </dependency>
         </dependencies>
         <build>
             <sourceDirectory>src/main/scala</sourceDirectory>
             <plugins>
                 <!-- 指定编译java的插件 -->
                 <plugin>
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-compiler-plugin</artifactId>
                     <version>3.5.1</version>
                 </plugin>
                 <!-- 指定编译scala的插件 -->
                 <plugin>
                     <groupId>net.alchim31.maven</groupId>
                     <artifactId>scala-maven-plugin</artifactId>
                     <version>3.2.2</version>
                     <executions>
                         <execution>
                             <goals>
                                 <goal>compile</goal>
                                 <goal>testCompile</goal>
                             </goals>
                             <configuration>
                                 <args>
                                     <arg>-dependencyfile</arg>
                                     <arg>${project.build.directory}/.scala_dependencies</arg>
                                 </args>
                             </configuration>
                         </execution>
                     </executions>
                 </plugin>
                 <plugin>
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-surefire-plugin</artifactId>
                     <version>2.18.1</version>
                     <configuration>
                         <useFile>false</useFile>
                         <disableXmlReport>true</disableXmlReport>
                         <includes>
                             <include>**/*Test.*</include>
                             <include>**/*Suite.*</include>
                         </includes>
                     </configuration>
                 </plugin>
                 <plugin>
                     <groupId>org.apache.maven.plugins</groupId>
                     <artifactId>maven-shade-plugin</artifactId>
                     <version>2.3</version>
                     <executions>
                         <execution>
                             <phase>package</phase>
                             <goals>
                                 <goal>shade</goal>
                             </goals>
                             <configuration>
                                 <filters>
                                     <filter>
                                         <artifact>*:*</artifact>
                                         <excludes>
                                             <exclude>META-INF/*.SF</exclude>
                                             <exclude>META-INF/*.DSA</exclude>
                                             <exclude>META-INF/*.RSA</exclude>
                                         </excludes>
                                     </filter>
                                 </filters>
                                 <transformers>
                                     <transformer
                                             implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                         <mainClass></mainClass>
                                     </transformer>
                                 </transformers>
                             </configuration>
                         </execution>
                     </executions>
                 </plugin>
             </plugins>
         </build>
      </project>
  
 

        2、数据展示

        3、代码编写

      package org.example.spark
      import org.apache.spark.rdd.RDD
      import org.apache.spark.{SparkConf, SparkContext}
      object word {
        def main(args: Array[String]): Unit = {
         //准备环境
          val conf = new SparkConf().setMaster("local[*]").setAppName("wordcount")
          val sc = new SparkContext(conf)
         //加载文件
          val rdd1: RDD[String] = sc.textFile("data/input/words.txt")
         // 处理数据
          val rdd2: RDD[String] = rdd1.flatMap(lp => {
            lp.split(" ")
          })
          val rdd3: RDD[(String, Int)] = rdd2.map(it => (it, 1))
          val rdd4: RDD[(String, Int)] = rdd3.reduceByKey((curr, agg) => curr + agg)
          val result: Array[(String, Int)] = rdd4.collect()
          result.foreach(i => println(i))
        }
      }
  
 

        4、本地运行

        注：单词统计案例本地效果如图所示 

二、集群运行spark程序

        1、修改代码

val rdd1: RDD[String] = sc.textFile("hdfs:///input/wordcount.txt")
 

rdd4.saveAsTextFile("hdfs://192.168.231.247:8020/output/output1")
 

        注：集群运行文件加载路径设置为hdfs，即每次集群运行从hdfs拿取数据，并将实时数据上传至hdfs

        2、打包jar

        注：双击maven中的package，maven会自动进行清除缓存，测试并打包为jar 

        3、找到项目路径中的jar包

        注：jar包大小最小的为不是带全部依赖的jar包，在集群运行不需要全部的依赖，即上传最小依赖的jar包即可 

        4、上传至linux

        注：此处使用xftp进行传输 jar包

        5、启动 hadoop 以及 spark 集群 

        6、进入spark安装目录下执行

bin/spark-submit --class org.example.spark.word --master spark://master:8020 /input/original-SparkDemo-1.0-SNAPSHOT.jar 
 

         注：单词统计集群运行如图所示

        7、进入hdfs  web端目录进行查看

Spark-两种运行方式（本地运行，提交集群运行）完成

文章来源: tuomasi.blog.csdn.net，作者：托马斯-酷涛，版权归原作者所有，如需转载，请联系作者。

原文链接：tuomasi.blog.csdn.net/article/details/122919106